Data Modeler

Role Description

The role will be responsible for designing conceptual, logical, and physical data models that support business pricing capabilities and analytical use cases.

The successful candidate will work within a Medallion Architecture (Bronze, Silver, Gold) implemented on Azure Databricks and Azure Data Factory, ensuring data products are scalable, governed, reusable, and aligned to enterprise standards.

Key Responsibilities

• Data Modelling & Design
• Lead the development and maintenance of enterprise conceptual, logical, and physical data models for Pricing Data Products.
• Establish and promote data modelling standards, patterns, and best practices across the programme.
• Own modelling artefacts and ensure consistency, quality, traceability, and compliance with enterprise data architecture principles.
• Define business entities, relationships, hierarchies, reference data structures, and business rules across pricing and insurance domains.
• Provide expert guidance on modelling approaches, including 3NF, dimensional, canonical, and domain-oriented data models.
• Review and approve modelling deliverables produced by designers and engineering teams.
• Mentor junior data modellers and contribute to capability development within the data community.
• Data Product Design
• Design data structures across Bronze, Silver, and Gold layers within a Medallion Architecture.
• Define reusable data assets and data products that support pricing, commercial, and financial reporting use cases.
• Ensure data products support scalability, performance, data quality, and lineage requirements.
• Collaborate with Product Owners and Data Architects to align data models with business outcomes.
• Azure Databricks & Data Engineering Collaboration
• Work closely with Data Engineers to implement data models using Azure Databricks and Delta Lake.
• Create transformation logic specifications suitable for PySpark implementation.
• Review data pipelines and transformations to ensure compliance with approved data models.
• Support optimization of data structures for performance and analytical consumption.
• Data Governance & Quality
• Define data quality rules, validation checks, and reconciliation requirements.
• Ensure metadata, lineage, and business glossaries are maintained.
• Support data governance frameworks and master/reference data standards.
• Contribute to data catalogue and metadata management activities.

Required Skills

• Strong experience in conceptual, logical, and physical data modelling.
• Experience designing enterprise-scale data products and analytical data models.
• Proficiency with data modelling methodologies and best practices.
• Experience creating source-to-target mappings and transformation specifications.
• Excellent communication and stakeholder management skills.
• Experience with data governance and metadata management tools.
• Advanced SQL skills.
• Understanding of data profiling, reconciliation, and validation techniques.
• Experience analysing complex datasets and resolving data quality issues.
• Good understanding of Medallion Architecture
• Good understanding of Data Mesh principles
• Good understanding of Lakehouse architectures
• Good understanding of Master and Reference Data Management
• Good understanding of Data Governance frameworks
• Experience with data modelling tools (ERwin, ER/Studio, etc.)
• Understanding of Azure Data Services, Databricks, and ADF is desirable.
• Past insurance data domains experience is desirable.